In some implementations of crest factor reduction (CFR), peak magnitude in a signal may be determined. Such may be accomplished by oversampling the signal, identifying signal magnitudes that are larger than two neighboring magnitudes, and then testing to determine if any of the signal magnitudes exceeds a predetermined threshold. If the oversampling rate of the signal is low, then the peak magnitude may not be accurate and may deviate significantly from the true peak value. As the oversampling rate decreases, there is a corresponding decrease in the accuracy in the estimate of the peak magnitude. This reduction in the accuracy of the peak magnitude estimate directly affects the quality of the CRF method. In some cases, the location of the detected peak and the complex signal value at the detected peak are required for peak cancellation crest factor reduction (PCCFR). Thus, accurate peak detection is important for PCCFR and CFR.
One method for implementing CFR is the cancellation pulse method. Although this method is effective, it suffers from the issue that some peaks may be missed and/or created during execution of the cancellation pulse method. In particular, in the cancellation pulse method, some peaks may be missed due to a lack resources for pulse cancelation. Additionally, new peaks may be undesirably created when cancellation pulses overlap and add constructively. In some cases, pulse cancellation may be repeated in the cancellation pulse method some number of times to address these undesirable peaks. However, each processing stage is comparatively expensive and adds significantly to the latency in the system that implements the CFR. This, in turn, negatively affects an efficiency and capacity of a base station that implements the CFR.
Peak detection may also be used in other areas, such as image processing, and automatic gain control. Also, other types of detectors, such as root mean square detector, log detector, etc., may benefit from the use of peak detection.